location-enrichment

location-enrichment is a skill for Claude Code from leopu00/job-hunter-team. It costs 86 tokens per session (2,701 once invoked), scanned A, original, MIT.

A procedure for turning free-text job locations into structured fields such as country, continent, work mode, and role category. It also records the contracting country, meaning the country of the entity signing the employment contract.

In plain words
What is it for?
It helps classify remote, hybrid, onsite, multi-location, Europe-wide, and country-specific jobs one position at a time.
Why use it?
It prevents inconsistent or incomplete location data and requires positions to be fully structured before they are marked as checked.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 /app/shared/skills/db_query.py raw \.

Good fit It helps classify remote, hybrid, onsite, multi-location, Europe-wide, and country-specific jobs one position at a time.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/leopu00/job-hunter-team
agentmods
npx agentmods add skills/leopu00/job-hunter-team/location-enrichment

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for location-enrichment

README.md
[![agentmods](https://agentmods.dev/badge/skills/leopu00/job-hunter-team/location-enrichment/github.svg)](https://agentmods.dev/skills/leopu00/job-hunter-team/location-enrichment)
Your own site
<a href="https://agentmods.dev/skills/leopu00/job-hunter-team/location-enrichment"><img src="https://agentmods.dev/badge/skills/leopu00/job-hunter-team/location-enrichment/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for location-enrichment

Your own site · 80×15
<a href="https://agentmods.dev/skills/leopu00/job-hunter-team/location-enrichment"><img src="https://agentmods.dev/badge/skills/leopu00/job-hunter-team/location-enrichment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,701 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 248
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00086 $0.02701
Opus 5 $0.00043 $0.01350
Sonnet 5 $0.00017 $0.00540
Haiku 4.5 $0.00009 $0.00270

Measured 12d ago against content hash 19ce635237e3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

location-enrichment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/_skills/location-enrichment/SKILL.md · 293 lines

How it starts

The opening of the file, as written. The whole thing — 293 lines — stays where its author put it; the contents beside it link to each section on GitHub.

location-enrichment — location + role_family structuring playbook

The Analista fills 11 columns of the positions table BEFORE marking status=checked. Never leave a position checked without location enrichment.

The 11 columns to fill

role_family         text   semantic category of the role
loc_city            text   office city (NULL if country only)
loc_region          text   region/state (optional)
loc_country         text   physical office country (NULL if continent only)
loc_country_code    text   ISO-3166 alpha-2: IT, IE, HU, ...
loc_continent       text   Europe | Asia | Americas | Africa | Oceania
work_mode           text   onsite | hybrid | remote
work_country        text   contracting country (the signing entity) — NEVER NULL
work_country_code   text   ISO-2 of work_country
is_multi_location   bool   true if the JD lists several cities/countries
location_notes      text   analyst free-text notes

Behavioural RULES (CRITICAL — sim 1-2 found problems here)

R1 — One position at a time (NO BATCH)

Process your range one position per turn: read the JD → reason → db-update → status=checked → next. Do NOT load 20+ JDs in a single LLM turn. Exception: 3-5 trivial cases with no web search (e.g. "Dublin, Ireland" + hybrid).

Why: a 17k+ token batch (sim 1) produces generic responses ("multi-location + remote + EU") instead of data specific to each record. And the other analysts spin idle during your mega-turn.

R2 — Peer DB taxonomy lookup (every 5-10 records)

BEFORE picking a role_family value, check what your colleagues have used:

python3 /app/shared/skills/db_query.py raw \
  "SELECT role_family, COUNT(*) AS n FROM positions
   WHERE role_family IS NOT NULL
   GROUP BY role_family ORDER BY n DESC"

If you find a semantically equivalent family, ALIGN to their name. Wrong examples seen in sim 1:

✗ "Translation / Localization" vs "Localization / Language Quality"
  vs "Language / Localization"           → only one
✗ "Customer Support" vs "Customer Success / Technical"
  vs "Technical Support"                 → only one
✗ "Technical Engineering" for a Technical Writer   → wrong

Read the full file on GitHub · 293 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 293 lines · 86 tokens per session scan A 19ce635237e3

Subscribe to this mod's changes

location-enrichment is a skill published in the GitHub repository leopu00/job-hunter-team (49 stars, last pushed yesterday), licensed MIT. It adds 86 tokens to every session and 2,701 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.